app.py

import gradio as gr
import numpy as np
import io
from pydub import AudioSegment
import tempfile
import openai
import time
from dataclasses import dataclass, field
from threading import Lock
import base64
import uuid
import os


@dataclass
class AppState:
    stream: np.ndarray | None = None
    sampling_rate: int = 0
    conversation: list = field(default_factory=list)
    client: openai.OpenAI = None
    output_format: str = "mp3"


# Global lock for thread safety
state_lock = Lock()


def create_client(api_key):
    return openai.OpenAI(
        base_url="https://llama3-1-8b.lepton.run/api/v1/", api_key=api_key
    )


def test_api_key(client):
    # Try making a simple request to check if the API key works
    try:
        # Attempt to retrieve available models as a test
        client.models.list()
    except Exception as e:
        raise e


def process_audio(audio: tuple, state: AppState):
    if state.stream is None:
        state.stream = audio[1]
        state.sampling_rate = audio[0]
    else:
        state.stream = np.concatenate((state.stream, audio[1]))

    return state  # Only state is returned


def update_or_append_conversation(conversation, id, role, new_content):
    for entry in conversation:
        if entry["id"] == id and entry["role"] == role:
            entry["content"] = new_content
            return
    conversation.append({"id": id, "role": role, "content": new_content})


def generate_response_and_audio(audio_bytes: bytes, state: AppState):
    if state.client is None:
        raise gr.Error("Please enter a valid API key first.")

    format_ = state.output_format
    bitrate = 128 if format_ == "mp3" else 32  # Higher bitrate for MP3, lower for OPUS
    audio_data = base64.b64encode(audio_bytes).decode()
    old_messages = []

    for item in state.conversation:
        old_messages.append({"role": item["role"], "content": item["content"]})

    old_messages.append(
        {"role": "user", "content": [{"type": "audio", "data": audio_data}]}
    )

    try:
        stream = state.client.chat.completions.create(
            extra_body={
                "require_audio": True,
                "tts_preset_id": "jessica",
                "tts_audio_format": format_,
                "tts_audio_bitrate": bitrate,
            },
            model="llama3.1-8b",
            messages=old_messages,
            temperature=0.7,
            max_tokens=256,
            stream=True,
        )

        full_response = ""
        asr_result = ""
        final_audio = b""
        id = uuid.uuid4()

        for chunk in stream:
            if not chunk.choices:
                continue
            content = chunk.choices[0].delta.content
            audio = getattr(chunk.choices[0], "audio", [])
            asr_results = getattr(chunk.choices[0], "asr_results", [])
            if asr_results:
                asr_result += "".join(asr_results)
                yield id, full_response, asr_result, None, state
            if content:
                full_response += content
                yield id, full_response, asr_result, None, state
            if audio:
                final_audio = b"".join([base64.b64decode(a) for a in audio])
                yield id, full_response, asr_result, final_audio, state

        yield id, full_response, asr_result, final_audio, state

    except Exception as e:
        raise gr.Error(f"Error during audio streaming: {e}")


def response(state: AppState):
    if state.stream is None or len(state.stream) == 0:
        return None, None, state

    audio_buffer = io.BytesIO()
    segment = AudioSegment(
        state.stream.tobytes(),
        frame_rate=state.sampling_rate,
        sample_width=state.stream.dtype.itemsize,
        channels=(1 if len(state.stream.shape) == 1 else state.stream.shape[1]),
    )
    segment.export(audio_buffer, format="wav")

    generator = generate_response_and_audio(audio_buffer.getvalue(), state)

    for id, text, asr, audio, updated_state in generator:
        state = updated_state
        if asr:
            update_or_append_conversation(state.conversation, id, "user", asr)
        if text:
            update_or_append_conversation(state.conversation, id, "assistant", text)
        chatbot_output = state.conversation
        yield chatbot_output, audio, state

    # Reset the audio stream for the next interaction
    state.stream = None


def set_api_key(api_key, state):
    try:
        state.client = create_client(api_key)
        test_api_key(state.client)  # Test the provided API key
        api_key_status = gr.update(value="API key set successfully!", visible=True)
        api_key_input = gr.update(visible=False)
        set_key_button = gr.update(visible=False)
        return api_key_status, api_key_input, set_key_button, state
    except Exception as e:
        api_key_status = gr.update(
            value="Invalid API key. Please try again.", visible=True
        )
        return api_key_status, None, None, state


def initial_setup(state):
    api_key = os.getenv("API_KEY")
    if api_key:
        try:
            state.client = create_client(api_key)
            test_api_key(state.client)  # Test the API key from the environment variable
            api_key_status = gr.update(
                value="You are using default Lepton API key, which have 10 requests/min limit",
                visible=True,
            )
            api_key_input = gr.update(visible=False)
            set_key_button = gr.update(visible=False)
            return api_key_status, api_key_input, set_key_button, state
        except Exception as e:
            # Failed to use the api_key, show input box
            api_key_status = gr.update(
                value="Failed to use default API key. Please enter a valid API key.",
                visible=True,
            )
            api_key_input = gr.update(visible=True)
            set_key_button = gr.update(visible=True)
            return api_key_status, api_key_input, set_key_button, state
    else:
        # No API key in environment variable
        api_key_status = gr.update(visible=False)
        api_key_input = gr.update(visible=True)
        set_key_button = gr.update(visible=True)
        return api_key_status, api_key_input, set_key_button, state


with gr.Blocks() as demo:
    gr.Markdown("# Lepton AI LLM Voice Mode")
    gr.Markdown(
        "You can find Lepton AI LLM voice doc [here](https://www.lepton.ai/playground/chat/llama-3.2-3b) and serverless endpoint API Key [here](https://dashboard.lepton.ai/workspace-redirect/settings/api-tokens)"
    )
    with gr.Row():
        with gr.Column(scale=3):
            api_key_input = gr.Textbox(
                type="password",
                placeholder="Enter your Lepton API Key",
                show_label=False,
                container=False,
            )
        with gr.Column(scale=1):
            set_key_button = gr.Button("Set API Key", scale=2, variant="primary")

    api_key_status = gr.Textbox(
        show_label=False, container=False, interactive=False, visible=False
    )

    with gr.Blocks():
        with gr.Row():
            input_audio = gr.Audio(
                label="Input Audio", sources="microphone", type="numpy"
            )
            output_audio = gr.Audio(label="Output Audio", autoplay=True, streaming=True)
        chatbot = gr.Chatbot(label="Conversation", type="messages")

    state = gr.State(AppState())

    # Initial setup to set API key from environment variable
    demo.load(
        initial_setup,
        inputs=state,
        outputs=[api_key_status, api_key_input, set_key_button, state],
    )

    set_key_button.click(
        set_api_key,
        inputs=[api_key_input, state],
        outputs=[api_key_status, api_key_input, set_key_button, state],
    )

    stream = input_audio.stream(
        process_audio,
        [input_audio, state],
        [state],
        stream_every=0.25,  # Reduced to make it more responsive
        time_limit=60,  # Increased to allow for longer messages
    )

    respond = input_audio.stop_recording(
        response, [state], [chatbot, output_audio, state]
    )
    # Update the chatbot with the final conversation
    respond.then(lambda s: s.conversation, [state], [chatbot])


demo.launch()